TY - GEN
T1 - Option pricing using a committee of neural networks and optimized networks
AU - Dindar, Zaheer A.
AU - Marwala, Tshilidzi
PY - 2004
Y1 - 2004
N2 - The derivative market has seen tremendous growth in recent times. We look at a particular area of these markets, viz. options. The pricing of options has its roots in stochastic mathematics since option pricing data is highly non-linear. It seems obvious to apply the training techniques of neural networks to this type of data. The standard Multi-Layer Perceptron (MLP) and Radial Basis Functions (RBF) were used to model the data; these results were compared to the results found by using a committee of networks. The MLP and RBF architecture was then optimized using Particle Swarm Optimization (PSO). The results from the 'optimal architecture' networks were then compared to the standard networks and the committee network. We found that, at the expense of computational time, the 'optimal architecture' RBF and MLP networks achieved better results than both unoptimized networks and the committee of networks.
AB - The derivative market has seen tremendous growth in recent times. We look at a particular area of these markets, viz. options. The pricing of options has its roots in stochastic mathematics since option pricing data is highly non-linear. It seems obvious to apply the training techniques of neural networks to this type of data. The standard Multi-Layer Perceptron (MLP) and Radial Basis Functions (RBF) were used to model the data; these results were compared to the results found by using a committee of networks. The MLP and RBF architecture was then optimized using Particle Swarm Optimization (PSO). The results from the 'optimal architecture' networks were then compared to the standard networks and the committee network. We found that, at the expense of computational time, the 'optimal architecture' RBF and MLP networks achieved better results than both unoptimized networks and the committee of networks.
KW - Multi-layer Perceptron (MLP)
KW - Options
KW - Particle Swarm Optimization
KW - Radial Basis Functions (RBF)
UR - http://www.scopus.com/inward/record.url?scp=15744403180&partnerID=8YFLogxK
U2 - 10.1109/ICSMC.2004.1398336
DO - 10.1109/ICSMC.2004.1398336
M3 - Conference contribution
AN - SCOPUS:15744403180
SN - 0780385667
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 434
EP - 438
BT - 2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
T2 - 2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
Y2 - 10 October 2004 through 13 October 2004
ER -